Reproduce “Deploy-Master: Automating the Deployment of 50,000+ Agent-Ready Scientific Tools in One Day” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
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About this paper
Yi Wang, Zhenting Huang, Zhaohan Ding, Ruoxue Liao, Yuan Huang, Xinzijian Liu, Jiajun Xie, Siheng Chen and 1 more
DEPLOY-MASTER introduces an agentic workflow to automate the transformation of over 50,000 heterogeneous open-source scientific software repositories into runnable, reproducible, and agent-ready tools. The system achieved a 95.36% deployment success rate, building a unified hub of execution-validated capabilities for AI for Science and agentic research.
Key insights
- Automated, large-scale deployment of diverse scientific tools is feasible with high success rates (95.36%) through an execution-centered, agentic approach, rather than relying solely on explicit documentation.
- The primary challenge in operationalizing scientific software is 'specification uncertainty' (incomplete/inconsistent build instructions), not limitations of container technology or basic infrastructure.
- While most tools build efficiently (median under ten minutes), a significant 'long tail' in build times highlights the variability in complexity and resource demands across the scientific software landscape.
Summary by alphaXiv.
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